A universal all-solid synthesis for high throughput production of halide perovskite

Halide perovskites show ubiquitous presences in growing fields at both fundamental and applied levels. Discovery, investigation, and application of innovative perovskites are heavily dependent on the synthetic methodology in terms of time-/yield-/effort-/energy- efficiency. Conventional wet chemistry method provides the easiness for growing thin film samples, but represents as an inefficient way for bulk crystal synthesis. To overcome these, here we report a universal solid state-based route for synthesizing high-quality perovskites, by means of simultaneously applying both electric and mechanical stress fields during the synthesis, i.e., the electrical and mechanical field-assisted sintering technique. We employ various perovskite compositions and arbitrary geometric designs for demonstration in this report, and establish such synthetic route with uniqueness of ultrahigh yield, fast processing and solvent-free nature, along with bulk products of exceptional quality approaching to single crystals. We exemplify the applications of the as-synthesized perovskites in photodetection and thermoelectric as well as other potentials to open extra chapters for future technical development.


Supplementary Notes Supplementary Note 1 TRPL average lifetime
We measured the TRPL spectra of thin film, powder, and FAST-MAPbI3 using a 505 nm femtosecond laser as excitation light source and a time-correlated single photon counting detector for signal collection.

Reconvolution
After obtaining the raw data, instrument response function (IRF) spectra was also obtained to correct the spectra of sample of interest. This is because for real lifetime measurements, the IRF, ( ), is not infinitely small. The shape and width of the ( ) are the results from the excitation light pulse (e.g., duration, shape) as well as the response time of the instrument. In typical, the decay of photocarrier can be modeled by exponential model (e.g., a single e.g., ( ) = − , with being the scalar factor, and being the characteristic lifetime, respectively). In certain cases when the characteristic lifetime of the sample falls in the range of IRF, the samples intrinsic attribute can ( ( )) deviate from the measured result of ( ( )), in a convolutional relationship with IRF involved 1,2 . This relationship can be expressed by the equation of (1) Hence, through the reconvolution of ( ) by IRF, intrinsic sample performance of ( ) can be accurately quantified.

Fitting Algorithm
For the TRPL fitting process, we utilized the bi-exponential decay function of where 1 is the fast decay lifetime component, 1 is the fast decay amplitude, 2 is the slow decay lifetime component, 2 is the slow decay amplitude, and is a constant, respectively. Levenberg-Marquardt algorithm (LMA) is used for seeking the best fitting parameters, and evaluated by the parameter of: Where the is the weighting factor, is the fitting value and is the experimental value, is the number of free parameters approximately to the number subtracted from the fitted data points by the number of lifetime parameters used in the fitting. 2 has a theoretical limit 1.0 for Poissonian distributed and in typical, 2 needs to be less than 1.0 to secure a good fitting. Higher order exponential decay can lead to a smaller 2 , i.e., better fitting. While choosing the decay model also needs to take consideration of the sample condition. In this work, we utilized the biexponential decay because it already exhibited a good fit by showing 2 of < 0.5. Additionally, for MAPbI3, it has been widely reported both surface trap and bulk defect can lead to relative quick and slow decay component in the TRPL 3 . This well-agreed model is also consistent to the result observed in this work. Hence, we employ the bi-exponential decay function to quantify these underlying attributes of the samples of interest.

Average lifetime
To extract a general photophysical attribute of different samples, we employed the intensityweighted average lifetime ( ) to quantify the results. Since the PL intensity contribution of a component is proportional to the product , the intensity-weighted average lifetime ( ) is defined as 4 This intensity-weighted average lifetime ( ) can also be defined as the average lifetime of a collection of different excited-state populations. The lifetime of each population is weighted by the relative contribution of that population to the total PL. For halide perovskites, both surface trap (fast component) and bulk defect (slow component) could contribute different population to the overall fluorescence. To include both contributions, we use this intensity-weighted average lifetime ( ) to quantify the sample quality. The detailed data are shown in Supplementary  Table 1.
Briefly, for halide perovskites, both surface trap (faster component) and bulk defect (slower component) could contribute different population to the overall fluorescence. As can be seen in the Supplementary Table 1, all the three samples of thin-film, powder, and FAST-MAPbI3 show similar ratio of A1 and A2, which makes it easier to directly compare faster and slower lifetime. Along the surface trap-induced decay, the FAST-samples display the longest lifetime of 72.4 nm compared to thin film (30.2 ns) and powder (6.7 ns). This is consistent to the high trap density nature of the powder and indicates the FAST sample has less surface trap detrimental effect compared to the film sample. Similarly, from the perspective of bulk trap induced decay, the FAST sample also shows longest lifetime of 311 ns, compared to 63 and 77 ns of powder and thin film samples, respectively. This also suggests the high quality of the FAST sample in bulk. While for single crystal sample, as the ratio of A1 and A2 is different from the other three samples, it is hard to directly compare the 1 and 2 . Hence, the can be a more proper figure-of-merit to evaluate the lifetime. Apparently, single crystal sample shows a smallest value of 20.7 ns. This is more likely due to the presence of hypothetical solvent impurity, surface microstructure and point defect as discussed in previous text in this response file.

Supplementary Note 2 Trap density and hole mobility
To investigate the trap density and charge carrier mobility of the samples, we utilized the spacecharge-limited current (SCLC) method by measuring the dark I-V curve on the hole-only device of Au/FAST-MAPbI3/Au. The hole-only device was fabricated by sequential deposition of 100 nm thick Au layers on the both sides of FAST-MAPbI3 sample. The active area ( ) is defined to be 0.56 cm 2 and the thickness ( ) of FAST-MAPbI3 disk is 1.33 mm. The I-V curve is listed as Fig. 2D in the main text, where there are three regions: in the low-bias region, a linear relationship between current density and voltage is observed which is corresponding to an ohmic response; as the voltage develops the current density shows a nonlinear increase which is corresponding to the trap-filling due to the injected charge carriers; at higher voltage region, the current increases quadratically along with the voltage, which is usually termed by "Child regime" that is typically used to describe the space-charge-limited current (SCLC) in a plane-parallel vacuum diode with the dependence of voltage (three-halves power) 5 .
In the trap filling region (or trap-filled limit (TFL) regime), the traps in the material have all been filled prior to the application of voltage. There is a voltage threshold of VTFL (noted in Fig. 2D) for current flow, which is because that before applying the voltage there already exist unneutralized charges at the traps which will further prevent the electron injection at the electrode. It is thus necessary for the charges to overcome this repulsion by a voltage of VTFL. The mathematical treatment of the TFL law can be referred to a prior paper 6 . In consequence, VTFL can be expressed by the equation of: Where the is the elementary charge, 0 and are the relative permittivity of free space and perovskite, is the trap density, and is the sample thickness, respectively. Then the trap density can be obtained from equation. We calculated the result to be 5.4×10 10 cm -3 , for the FAST-MAPbI3 sample, which is comparable to those of single-crystals ( Fig. 2E) and ca. 5-order of magnitude lower than those in solution-processed polycrystals (Fig. 2E).
In the Child region, the Child behavior does not generally apply to a semiconductor/insulator in a single-carrier device. And the Mott-Gurney law 7,8 is used to quantify the J-V behavior in such situation. Considering the perovskite disk of thickness of L, the current density voltage relationship can be described by the equation of: Where 0 and are the relative permittivity of free space and perovskite, is the voltage and is the current density. The charge carrier mobility can be calculated by the equation of: The hole mobility of the FAST-MAPbI3 disk was calculated to be 1.7 cm 2 V -1 s -1 , which is also similar to the values of single-crystal samples (Fig. 2E) and shows great consistence to its low trap-density feature.

Supplementary Note 3 Decomposition mechanism of Cs 2 SnI 6 and residual CsI in FAST sample.
The Cs2SnI6 perovskite is believed to exhibit higher air stability compared to other Sn 2+ -based Pbfree halide perovskites because of the oxidation state of Sn 4+ in the lattice. Prior reports demonstrated that the Cs2SnI6 is stable in the ambient of low relative humidity (RH) (30-50% RH), exhibiting no obvious decomposition over two months 9 . Nevertheless, the CsI can be present in the thin film sample rapidly due to high RH or aqueous conditions. Prior studies report a threshold RH of 80% 10 , above which the Cs2SnI6 could decompose into CsI and SnI4, followed by sequential reaction to form Sn(OH)4 by moisture adsorption. The process can be expressed by: Cs2SnI6 ↔ SnI4 + CsI (8) SnI4 + H2O ↔ Sn(OH)4+ HI (9) High RH will push the proceeding of Supplementary Equation 9 to right side, this will facilitate the proceeding of Supplementary Equation 8 to right side. As a result, CsI will be left. Particularly for nanoparticles (or powder sample of Cs2SnI6 obtained from BM process), multiple defects can be presented at the particle surface. These dislocation defects can be further developed in to 'etch pits' which accelerate the crystal degradation.
Hence, before consolidation into bulk sample by FAST, the Cs2SnI6 powders (nanocrystals) provides many active sites ('etch pits') allowing fast reaction with moisture. This is the reason why even using stoichiometric precursors, the FAST-Cs2SnI6 still has the CsI peaks (they were formed before the FAST). Only by adding extra SnI4 as sacrifice agent, the final sample did not show the CsI peaks. In the meantime, we also track the degradation of the after FAST samples. After FAST, we observed a higher air stability of the consolidated samples (than the powder sample), which is due to that the compact disk sample has less such nanoscopic defects, and consequently lower probability of degradation.

Supplementary Note 4 Lattice Thermal Conductivity ( ) Calculation
Lattice thermal conductivity ( ) can be calculated via subtracting the electronic contribution ( ) from the total thermal conductivity ( ), by the equation of 11 : = − (10) And can be estimated from the Wiedemann-Franz relation 12 , through the equation of: = (11) Where is the Lorenz factor, is the electrical conductivity, and is is the temperature. Direct measurement of requires a high mobility and remains difficult thus is typically estimated either as a constant (i.e., 2.44 × 10 −8 WΩK −2 in case of metal), or via a transport model (e.g., single parabolic band (SPB) model that can be obtained by solving Boltzmann transport equations-to experimental data). Under this condition, both Lorenz factor ( ) and Seebeck coefficient ( ) are the functions of reduced Ferimi level (or reduced chemical protentional ( ) and carrier scattering factor ( ). (i) For Seebeck coefficient ( ): starting from Fermi-Dirac distribution (considering one-type carrier transport and for a parabolic band with being a scattering parameter, there is ( ) = 0 , where 0 is a constant), one can derive to the following equation set 13 : Where is the Seebeck coefficient, is the Boltzmann constant, is the elementary charge, is relevant to scattering parameter by = + 3/2, and and ( ) are the reduced Fermi level and integration respectively and can be determined by: Where is the Ferimi level, and E is a cut-off energy level below which all the electrons are completely blocked from participating in conduction.
For simplicity, we estimate The heating process takes less than 2 min and cooling ramp takes slightly more time (e.g., 3-5 min). Notably, all the parameters can be adjusted as the FAST set up is customized in lab, extra pressure or temperature range, or more precise control can be incorporated as well. It goes in opposite rotation direction to the jars due to the different rotational axes of the main disk and the milling jars. This reversed rotation creates a 'D shape' movement of balls inside the jar under the influence of Coriolis and centrifugal forces. In this scenario, kinetic energy within the jars is supposed to increase and lead to high energy ball-to-ball and ball-to-wall impacts, which will effectively grind and blend the perovskite precursors. d Pictures showing the precursor powders of MAI and PbI2 before BM. e Picture showing the black MAPbI3 powder after BM. The easy reaction between precursors, plus the high kinetic energy provides the quick conversion from precursors into the black powder. We also carry out the material characterizations on the BMsynthesized powder of MAPbI3, which will be discussed in the next figure. f The photo of the BM setup. It should be noted that there is negligible difference between the BM samples under 12 min and 24 min. This is also supported by the XRD spectra where all the scattering peaks are assigned to the corresponding lattice plane of the MAPbI3, and no impurity peaks of PbI2 observed, which however occurs in certain solution-processed method in prior studies. As a result, we anticipate 12 min high energy BM process is enough to execute the complete reaction between the precursors. We compared the XRD spectra of FAST and powder MAPbI3, with calculated XRD patterns from lattice of cubic and tetragonal models. The results show that the FAST-sample exhibits the emergence of (00l) dominated planes compared to the powders. In addition, evidence of the emerging planes of (200) and (210)  with dependence of photo energy (ℎ ), with being the absorption coefficient, ℎ being the Planck's constant, and being the frequency of the light wave. According to Jan Tauc, the extrapolation of the linear region to the abscissa gives the energy of the optical bandgap of the material of interest. Depending on different type of materials, the order index needs to be adjusted accordingly. In this study, we obtained the Tauc plot from the UV-vis absorption spectra. The MAPbI3 displays a direct band gap feature 16 , which assigns the to be 1/2. As a result, we calculated the optical bandgap of the FAST-MAPbI3 to be 1.46 eV. This value is smaller than the typical number of thin film samples (e.g., ~1.6 eV) 17 , and closer to that of single crystals (e.g., 1.51 eV) 18 . Prior study proposed an indirect transfer mechanism to explain the smaller bandgap in thicker perovskite samples 19 . This can also be due to other effects such as spin-orbital coupling that induces Rashba splitting, and/or lattice distortion/phonon related effects that induced additional states close to the band edge 16 .

Supplementary Fig. 8 Manufacturing techniques for making FAST-MAPbI 3 photodetector. (A)
Laser scribing technique photograph with key components presented. We utilized a picosecond laser to minimize the thermal damage to the sample. The laser power, scan rate, multi-scan times, z-focus, etc., are carefully controlled to peel off the Au layer without damaging the sample underneath. X & y-tracks are used to move the sample stage. The laser path is pre-programed through the integrated software from the machine. We also controlled the laser spot size by optical focusing system and optical path system, which resulted a small channel length to 36 µm. The lateral device can also be applied as a solar cell. Although the original device has a symmetric MIM configuration, it is possible to induce an internal electric asymmetric (internal field) by hypothetical mechanisms of ionic motion 20 (Supplementary Fig. 9c) and/or ferroelectric dipole polarization 21 (Supplementary Fig. 9d). As shown in Supplementary Fig. 9c, ion/vacancy within the lattice of the perovskites can be driven to move to the corresponding cathodes and anodes under the poling bias. After removal of the external poling bias, ions accumulated at corresponding electrodes can trigger the presence of an internal field which breaks the electric symmetry of the device. Similarly, the poling field can also induce the polarization of the electric dipole (either localized lattice distortion induced dipole or point defect induced dipole or other mechanisms) within the perovskites, which can also lead to the electric asymmetry of the device. Either of both mechanisms can lead to the internal electrical field that can drive the opposite motion of photo carriers. Accordingly, we measured the solar cell performance after poling the device under 8 V bias. The results show a solar cell power conversion efficiency (PCE) of 1.2%, with VOC of 0.71 V, JSC of 6.3 mA cm -2 , and FF of 27%. The relatively low performance is due to the lacking of proper buffer layers such as electron transfer layer (ETL) or hole transfer layer (HTL). Particularly the low FF of 27% is due to the poor selective extraction at the perovskite/gold interface that lacks sufficient barrier to block the reverse carrier transfer. Nevertheless, we found even using this simplest MIM device structure, the FAST device performance is still comparable with that of single-crystalline lateral device using C60/BCP buffers 22 (PCE of ~2% without interfacial optimization). with is the inter-electrode spacing, is the applied voltage, is the charge carrier mobility. The dropping time is related to the lifetime of the charge carriers within the device. We obtained both the raising time ( ) and dropping time ( ) from the normalized transient photocurrent of the FAST-MAPbI3 photodetector device, by using the current values variant from 10% to 90% of its maximal number (Supplementary Fig. 11). As a result, raising time ( ) and dropping time ( ) of 745 µs and 2.73 ms have been obtained, respectively, suggesting a quick photoresponse, significantly more rapid than those of traditional In2Se3 and several ZnO-based photodetectors 24,25 . We also compared these characteristic times of our FAST-device with those of state-of-the-art solution-processed perovskite devices from prior reports (Supplementary Table 2). As can be seen in Supplementary Table 2, the raising time of the FAST-device is comparable to those of single crystalline perovskite devices, suggesting a fast transport behavior of the charge carriers in the FAST sample. To further reduce the response time, one possible solution is to shrink the active layer thickness. Since FAST-MAPbI3 has a large thickness of 1.33 mm (compared to 100s nm scale of typical state-of-the-art perovskite photodetectors) but still exhibits small raising time, which allows sufficient space (e.g., reducing the thickness, or adding charge selective layers to accelerate the interfacial extraction, etc.) to further reduce the response time of the device.
On the other hand, from the raising time, the charge carrier mobility can also be estimated. The calculated mobility from this transient raising method is 44.9 cm 2 V -1 s -1 , which is one order of magnitude higher than the number estimated from the SCLC method. This discrepancy might be ascribed to different measuring methods that require certain boundary conditions or equation application precondition of the model that can be slightly deviated from the real device. Nevertheless, regardless of the measuring methods, the mobility number of the SCLC-MAPbI3 is still in the range of the single crystal. Supplementary Fig. 12 Characterizations of (Bi 2 Te 3 ) 0.1 (MAPbI 3 ) 0.9 alloy. a SEM image showing the perovskite grain being surrounded by the Bi2Te3, b XRD pattern displaying both sets of scattering planes of perovskite and Bi2Te3, and c a corresponding EDS mapping of (Bi2Te3)0.1(MAPbI3)0.9: (i) element mapping of both Pb and Te in the alloy. Separate element mapping of (ii) Pb and (iii) Te (EDS peaks of Bi and Pb locate closely with each other and difficult to distinguish Bi from Pb). From the Supplementary Fig. 12c, the alloy shows a well dispersion of perovskite particles in the matrix of Bi2Te3, with the size of hundreds of nanometers to ca. 7 μm. From the individual element mapping, for example of Pb (Supplementary Fig. 12c (ii)), there is a continuous map of Pb covering the whole SEM image area, suggesting a well dispersion of perovskite over the whole sample. Overall, the results show the dispersion of perovskite in the Bi2Te3 is uniform and no impurities or interference induced new phased emerged (as evidenced by the XRD in Supplementary Fig. 12b).

Supplementary Fig. 13 Thermoelectric properties of the FAST-(Bi 2 Te 3 ) x (MAPbI 3 ) 1-x alloys.
a Electrical conductivity ( ), b Seebeck coefficient ( ), c thermal conductivity ( ), and d ZT value. In general, compared to bismuth telluride which is metallic material with high electrical and thermal conductivity but low Seebeck coefficient, halide perovskites are more insulative with low electrical and thermal conductivity but high Seebeck coefficient. However, the magnitude of electrical conductivity is around 9 orders of magnitude but the compensation in Seebeck coefficient is around ca. 3 orders. Considering less than 1 order of magnitude lower thermal conductivity, the overall ZT ( = 2 ) of FAST-MAPbI3 is still ca. 2-order of magnitude lower than bismuth telluride. We study the two extreme cases of (Bi2Te3)x(MAPbI3)1-x, with x being 10% or 90%, to understand how the alloy feature can modulate the overall performance. As expected, all the alloy shows intermediate thermoelectric properties to their corresponding matrix only counterparts, suggesting no coupling effect. The SEM shows compact grain with barely noticeable grain boundaries. The grain exhibits large size over 10 µm. We also characterize the crystalline feature by XRD. The calculated XRD is based on a standard lattice model obtained from an online open database. We compared the results with corresponding scattering planes in Supplementary Fig. 15b. All the scattering peaks can be assigned to the corresponding lattice planes, without the presence of any impurity peaks. These results indicate the high quality of the FAST-Cs3Bi2I9. Supplementary Fig. 16 Proposed manufacturing of thermoelectric legs from FASTperovskites. a Conventional solution method which is of low material usage (ca. 30% yield) and long processing time (weeks level for growing large size crystal), representing a less efficient way for manufacturing. b FAST methods with 100% synthetic yield to a disk sample, but still exhibit material losses (80% yield in mechanical dicing) during dicing due to fringe loss and also failure due to the fragile nature of the material. c Proposed 3D printing technique using FAST-based methods for halide perovskites. A customized die can be predesigned which can be used to mold the perovskite thermoelectric leg. The cubic legs can then be directly used for device assembly. d Proposed 3D printing for semi-finished device (an p-n unit), where two dies containing n-type and p-type perovskites (can be realized by proper doping strategy) connected with a metal and conductive binder substrate. After FAST, the device can be ready to assembly into a p-n unit, which can be further assembled into an array. plane. This spatial arrangement of the localized electron density surrounding each atom can visualize the degree of phonon anharmonicity 27 in the lattice and thereby influence the lattice thermal conductivity ( ). As can be seen from Supplementary Fig. 19c, the map shows the localized dimensionless ELF probability density, with normalization from 0 to 1. The higher electronegative element of I (electronegativity of 2.66) attracts more charge than Sn (1.96), resulting negligible electrons surrounding Sn and hence a more ionic-like bond in the lattice. More importantly, nonspherical electron density for both I and Cs are present, which explains the origin of the large phonon anharmonicity in the lattice. This will increase the phonon scattering and thereby suppress the lattice thermal conductivity ( ). Such a phonon anharmonicity is typically used to explain the low in other halide materials 28,29 . Supplementary Fig. 21 The XRD spectra of the FAST-Cs 2.2 Sn 0.95 I 6 perovskite. The impurity peak of CsI is at 2θ of 27.6 °. As demonstrated in the main text, we found the stoichiometric Cs2SnI6-FAST sample still displays the impurity phase of CsI due to the fast nanostructure facilitated degradation during the BM sample preparation process. By reducing the CsI ratio in the precursors, the final FAST-Cs1.9Sn1.025I6 sample can exhibit purer phase without the presence of CsI (Fig. 4B(iii)). On the contrary, by adding extra CsI, such CsI XRD peak intensity increases. By compiling the results of XRD of different samples, it is concluded that the SnI4 is a sacrifice agent during the ball milling process. With about 5 mol% extra SnI4, the final product can keep a purer phase with minimized CsI impurity.
Interestingly, by using a stoichiometric ratio of precursor powder of CsI and SnI4, we observed an impurity XRD peak of CsI at 2θ of 27.58° (Fig. 4B(iii)). Notwithstanding the airstable nature of Cs2SnI6, this CsI impurity phase has been observed in many solution methods due to a quick decomposition from Cs2SnI6 to CsI which can be ascribe to the formation of micro etch pits 30,31 . This perhaps occurs during the transfer process between ball milling process and the FAST synthesis, as the milled nano/meso powder offers more etch pits to decompose the material. To avoid so, we adjust the ratio of precursors before milling and execute an identical FAST process for all the samples. Fig. 4B(iii) also compares XRD spectra of FAST samples from the stoichiometric to 2.5 mol% extra SnI4 and 5 mol% extra CsI. We found that addition of extra 2.5 mol% of SnI4 could stabilize the crystal during the milling and eventually eliminate the CsI impurity. In comparison, samples with more CsI (10 mol% extra) in the precursor brings more CsI to the final product (Supplementary Fig. 21). Supplementary Fig. 22 Thermoelectric properties of FAST-Cs 2.1 Sn 0.975 I 6 , Cs 2 SnI 6 , and Cs 1.9 Sn 1.025 I 6 , respectively. Temperature dependent (a) electrical conductivity ( ), (b) Seebeck coefficient ( ), (c) thermal conductivity ( ), and (d) ZT value. The FAST-Cs1.9Sn1.025I6 with purer phase shows an inferior electrical conductivity of 0.05 S cm -1 at 300 K, which is consistent with the cold-pressed Cs2SnI6 after annealing (ca. 0.01 S cm -1 ). Along with the addition of extra CsI, the electrical conductivity of the final FAST sample increases. The FAST-Cs2.1Sn0.975I6 exhibits the highest electrical conductivity of 1.04 S cm -1 at 469 K. All the FAST samples show a negative Seebeck coefficient revealing the n-type nature of the material.  (004) and (220) planes. c Comparison of fresh and 2-month age XRD, displaying the phase evolution. These results suggest robust feature of the EM-FAST MAPbI3 samples (no obvious degradation even after ambient storage for 2 months). The origin may come from the hypothetical lattice strain in these samples, which could increase the activation energy of ion migration 32,33 .
Supplementary Fig. 26 Stability study of the FAST FASnI 3 samples. a XRD results of a EM-FAST FASnI3 pellet stored in the ambient atmosphere for different time (RH 35-80%, depending on daily whether at State College, PA, United State, temperature of ca. 25 °C controlled by the lab). b Photography of the FASnI3 sample with different ages from 0 h to 24 h, exposed in ambient air. A degradation chemical reaction set is inserted to show the compositional evolution.
First of all, it is shown that in the case of storage inside of a glovebox, even after 1 year, the sample does not show any impurities or degradation peaks in the XRD. While storing in the ambient air, after 12 h there is emergence of SnI4 phase, and after 48 h there is emergence of SnO2 phase. This evolution is consistent to the sequential degradation process in the equation set in Supplementary  Fig. 26b. While from the photo, it is hard to observe obvious color change of the sample. This observation, together with the remaining scattering peaks of FASnI3 in the 48-h age sample in Supplementary Fig. 26a, suggest there could be a protection layer formed by the degrades covering the surface, which can prevent further degradation of the inner sample.

Supplementary Tables
Supplementary Table 1 Parameters of TRPL measurement for